Mammography Mass Detection System Based on Visual Attention Mechanism

Abstract

The invention discloses a mammogram mass detection system and detection method based on a visual attention mechanism, which mainly solves the problems of low detection rate and high false positive rate in the prior art. The whole system includes: image preprocessing module, feature extraction module, tumor detection module and detection result output module. The image preprocessing module preprocesses the original image; the feature extraction module extracts eigenvalues ​​from the preprocessed image; the mass detection module first generates a Gaussian pyramid of the feature map for the eigenvalues; and then processes the Gaussian pyramid to obtain a total saliency map; Finally, the total saliency map is segmented to obtain candidate suspicious masses and filter out false positive masses; the detection results are output through the detection result output module. The invention has the advantages of high detection rate and low false positive rate for breast X-ray image masses, and can be used for detection of interest regions of medical images and its auxiliary diagnosis.

Description

technical field

[0001] The invention belongs to the technical field of image processing, in particular to medical image processing, which can be used for the detection of regions of interest in medical images and its auxiliary diagnosis. Background technique

[0002] In recent decades, medical imaging has become one of the fastest-growing fields in medical technology. As a result, clinicians have a more direct and clear observation of internal lesions in the human body, and the diagnosis rate is also higher. Computer Aided Diagnosis (CAD for short) technology is known as the doctor's "second pair of eyes", researching how to effectively process these medical image information through image processing technology to assist doctors in diagnosis and even surgical planning etc., have significant social benefits and broad application prospects. Since the development of medical image processing technology as the key to computer-aided diagnosis, the crossover of various disciplines...

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